The matrix stick-breaking process for flexible multi-task learning

@inproceedings{Xue2007TheMS,
  title={The matrix stick-breaking process for flexible multi-task learning},
  author={Ya Xue and David B. Dunson and Lawrence Carin},
  booktitle={ICML},
  year={2007}
}
In multi-task learning our goal is to design regression or classification models for each of the tasks and appropriately share information between tasks. A Dirichlet process (DP) prior can be used to encourage task clustering. However, the DP prior does not allow local clustering of tasks with respect to a subset of the feature vector without making independence assumptions. Motivated by this problem, we develop a new multitask-learning prior, termed the matrix stick-breaking process (MSBP… CONTINUE READING
Highly Cited
This paper has 28 citations. REVIEW CITATIONS